| Summary: | 碩士 === 國立臺北科技大學 === 自動化科技研究所 === 95 === This thesis proposes a high speed auto-focusing strategy which dramatic increasing the speed and improving the reliability of the auto-focusing technique. This strategy integrates the fuzzy reasoning and grey prediction algorithm. Firstly, the local and global slopes of sharpness function, calculated by the specified image caught by CCD, are feeding into fuzzy reasoning scheme as input variables. The corresponding moving step is calculated from fuzzy reasoning scheme. Then, the gray prediction model is adapted to predict the peak of the sharpness function curve after the local or global slopes decreasing. Therefore, the focusing mechanism comes back to the previous position which is the focusing position. The strategy can reduce focusing time around the focusing position. Finally, an experimental setup, implemented on a PC with Microsoft windows and RTX subsystem, is installed to verify the performance of proposed strategy. Comparing the experimental results of proposed strategy with traditional binary-search algorithm, the results reveal that this strategy can reduce the focusing time.
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